Automatic assessment of pain based on deep learning methods: A systematic review.

Journal: Computer methods and programs in biomedicine
PMID:

Abstract

BACKGROUND AND OBJECTIVE: The automatic assessment of pain is vital in designing optimal pain management interventions focused on reducing suffering and preventing the functional decline of patients. In recent years, there has been a surge in the adoption of deep learning algorithms by researchers attempting to encode the multidimensional nature of pain into meaningful features. This systematic review aims to discuss the models, the methods, and the types of data employed in establishing the foundation of a deep learning-based automatic pain assessment system.

Authors

  • Stefanos Gkikas
    Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Estavromenos, Heraklion, 71410, Greece; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research & Technology-Hellas, Vassilika Vouton, Heraklion, 70013, Greece. Electronic address: gkikas@ics.forth.gr.
  • Manolis Tsiknakis
    Computational BioMedicine Laboratory, FORTH-ICS, Heraklion, Crete, Greece.